Optimized Lockdown Strategies for Curbing the Spread of COVID-19: A South African Case Study.
Ontology highlight
ABSTRACT:
SUBMITTER: Olivier LE
PROVIDER: S-EPMC8675548 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:IntroductionThe South African government enforced various alcohol sale restrictions during the COVID-19 lockdown in order to reduce hospital admissions related to alcohol-associated injuries. A cross-sectional study was performed to describe the temporal changes in trauma according to alcohol sale restrictions during the South African national COVID-19 lockdown.MethodsData from all trauma-related patients presenting to the emergency centre of Mitchells Plain Hospital from 01/03/2020 till 29/9/2020 and corresponding periods during 2019 were exported from an existing database. The relationship between variables was determined with the χ2-test, Fisher's exact test, independent samples median test or t-test. A sub-analysis compared similar 2020 lockdown levels when a second alcohol ban were instituted while most business were allowed to operate (level 3b - alcohol banned versus level 3 - alcohol restricted).ResultsTotal number of trauma presentations were 539 (14.6%) less in 2020 (n = 3160) than in 2019 (n = 3699); the mean number decreased by 2.5 per day (95% CI -2.9 to -2.1). Lockdown levels with an alcohol ban had on average 4.8 less patients per day than corresponding periods in 2019 (p < 0.001). No significant difference was observed in lockdown levels with alcohol sale restrictions (mean difference per day -0.4, p = 0.195). Trauma presentations increased significantly (mean difference per day 7.0 (95% CI 6.5 to 7.5)) from 2020 lockdown levels with alcohol sales ban (mean per day 11.4) to 2020 lockdown levels with alcohol sale restrictions (mean per day 18.4). Significantly less patients (mean -3.2 (95% CI -3.9 to -2.5)) presented during 2020 lockdown level 3b (alcohol sales banned, mean 13.9) compared to level 3 (alcohol sales restricted, mean 17.1).ConclusionTemporal changes in trauma were observed according to alcohol sale restrictions during South Africa's COVID-19 lockdown periods. Significantly less trauma cases presented during periods with an alcohol ban compared to periods where alcohol sales were only restricted.
| S-EPMC8410509 | biostudies-literature
Project description:BackgroundWith at least 94 countries undergoing or exiting lockdowns for contact suppression to control the COVID-19 outbreak, sustainable and public health-driven exit strategies are required. Here we explore the impact of lockdown and exit strategies in Singapore for immediate planning.MethodsWe use an agent-based model to examine the impacts of epidemic control over 480 days. A limited control baseline of case isolation and household member quarantining is used. We measure the impact of lockdown duration and start date on final infection attack sizes. We then apply a 3-month gradual exit strategy, immediately re-opening schools and easing workplace distancing measures, and compare this to long-term social distancing measures.FindingsAt baseline, we estimated 815 400 total infections (21.6% of the population). Early lockdown at 5 weeks with no exit strategy averted 18 500 (2.27% of baseline averted), 21 300 (2.61%) and 22 400 (2.75%) infections for 6, 8 and 9-week lockdown durations. Using the exit strategy averted a corresponding 114 700, 121 700 and 126 000 total cases, representing 12.07-13.06% of the total epidemic size under baseline. This diminishes to 9 900-11 300 for a late 8-week start time. Long-term social distancing at 6 and 8-week durations are viable but less effective.InterpretationGradual release exit strategies are critical to maintain epidemic suppression under a new normal. We present final infection attack sizes assuming the ongoing importation of cases, which require preparation for a potential second epidemic wave due to ongoing epidemics elsewhere.FundingSingapore Ministry of Health, Singapore Population Health Improvement Centre.
| S-EPMC7395828 | biostudies-literature
Project description:IntroductionDespite high levels of illicit trade in the tobacco market, the South African government banned the sale of tobacco products in March 2020 as part of its COVID-19 response. The ban lasted five months. We assess how the ban affected the cigarette market for a sample of smokers by comparing the price, consumption, and competitive landscapes before (March), during (May and June), and after (September) the ban.MethodsWe conducted three online surveys of cigarette smokers, asking about smoking behavior before, during, and after the ban. We use descriptive statistics and OLS regressions to estimate the impact of the ban on the South African cigarette market, focusing on the price of cigarettes.ResultsMost smokers continued smoking despite the sales ban. During the ban, prices increased by over 240%. Purchases shifted away from the normally dominant brands of the multinational tobacco companies to local/regional producers. The covariates of price changed substantially during the sales ban, the most pronounced being inter-provincial effects. After the ban, the market shifted back to its preban state, with an overall increase in price of 3.6%.ConclusionsCigarette sales continued despite the sales ban, further entrenching an already large illicit market. Had the government substantially increased the excise tax, rather than banned the sale of tobacco products, it would have achieved a similar public health outcome, received more revenue, and presumably not further entrenched the illicit market.ImplicationsSouth Africa temporarily banned the sale of tobacco as part of its COVID-19 response. Despite the ban, the sale of cigarettes did not cease; rather, it caused major disruption to the cigarette market. The ban inadvertently benefited manufacturers who were previously disproportionately involved in illicit activities; these manufacturers increased their market share even after the ban was lifted. The ban may have further entrenched South Africa's already large illicit market. Our results show that there are unintended consequences associated with a temporary ban on the sale of cigarettes.
| S-EPMC9383820 | biostudies-literature
Project description:We combine COVID-19 case data with mobility data to estimate a modified susceptible-infected-recovered (SIR) model in the United States. In contrast to a standard SIR model, we find that the incidence of COVID-19 spread is concave in the number of infectious individuals, as would be expected if people have inter-related social networks. This concave shape has a significant impact on forecasted COVID-19 cases. In particular, our model forecasts that the number of COVID-19 cases would only have an exponential growth for a brief period at the beginning of the contagion event or right after a reopening, but would quickly settle into a prolonged period of time with stable, slightly declining levels of disease spread. This pattern is consistent with observed levels of COVID-19 cases in the US, but inconsistent with standard SIR modeling. We forecast rates of new cases for COVID-19 under different social distancing norms and find that if social distancing is eliminated there will be a massive increase in the cases of COVID-19.
| S-EPMC7683602 | biostudies-literature
Project description:BackgroundSevere acute respiratory syndrome CoV-2 (SARS-CoV-2) caused the first coronavirus disease 2019 (COVID-19) outbreak in China and has become a public health emergency of international concern. SARS-CoV-2 outbreak has been declared a pandemic by WHO on March 11th, 2020 and the same month several Countries put in place different lockdown restrictions and testing strategies in order to contain the spread of the virus.MethodsThe calculation of the Case Fatality Rate of SARS-CoV-2 in the Countries selected was made by using the data available at https://github.com/owid/covi-19-data/tree/master/public/data . Case fatality rate was calculated as the ratio between the death cases due to COVID-19, over the total number of SARS-CoV-2 reported cases 14 days before. Standard Case Fatality Rate values were normalized by the Country-specific ρ factor, i.e. the number of PCR tests/1 million inhabitants over the number of reported cases/1 million inhabitants. Case-fatality rates between Countries were compared using proportion test. Post-hoc analysis in the case of more than two groups was performed using pairwise comparison of proportions and p value was adjusted using Holm method. We also analyzed 487 genomic sequences from the GISAID database derived from patients infected by SARS-CoV-2 from January 2020 to April 2020 in Italy, Spain, Germany, France, Sweden, UK and USA. SARS-CoV-2 reference genome was obtained from the GenBank database (NC_045512.2). Genomes alignment was performed using Muscle and Jalview software. We, then, calculated the Case Fatality Rate of SARS-CoV-2 in the Countries selected.ResultsIn this study we analyse how different lockdown strategies and PCR testing capability adopted by Italy, France, Germany, Spain, Sweden, UK and USA have influenced the Case Fatality Rate and the viral mutations spread. We calculated case fatality rates by dividing the death number of a specific day by the number of patients with confirmed COVID-19 infection observed 14 days before and normalized by a ρ factor which takes into account the diagnostic PCR testing capability of each Country and the number of positive cases detected. We notice the stabilization of a clear pattern of mutations at sites nt241, nt3037, nt14408 and nt23403. A novel nonsynonymous SARS-CoV-2 mutation in the spike protein (nt24368) has been found in genomes sequenced in Sweden, which enacted a soft lockdown strategy.ConclusionsStrict lockdown strategies together with a wide diagnostic PCR testing of the population were correlated with a relevant decline of the case fatality rate in different Countries. The emergence of specific patterns of mutations concomitant with the decline in case fatality rate needs further confirmation and their biological significance remains unclear.
| S-EPMC7463225 | biostudies-literature
Project description:IntroductionUsing digital technology to provide support, medical consultations, healthcare services, and to track the spread of the coronavirus has been identified as an important solution to curb the transmission of the virus. This research paper aims to (1) summarize the digital technologies used during the COVID-19 pandemic to mitigate the transmission of the COVID-19; (2) establish the extent to which digital technology applications have facilitated mitigation of the spread of COVID-19; and (3) explore the facilitators and barriers that impact the usability of digital technologies throughout the pandemic.MethodsA rapid electronic search following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines was conducted of available records up to June 2022 on the medical databases PubMed, Ovid, Embase, CINHAIL, the Cochrane Library, Web of Science, and Google Scholar.ResultsAn increasing number and variety of digital health applications have been available throughout the pandemic, such as telehealth, smartphone mobile health apps, machine learning, and artificial intelligence. Each technology has played a particular role in curbing COVID-19 transmission. Different users have gained benefits from using digital technology during the COVID-19 pandemic and different determinants have contributed to accelerating the wheel of digital technology implementation during the pandemic.ConclusionDigital health during the COVID-19 pandemic has evolved very rapidly, with different applications and roles aimed at curbing the pandemic.
| S-EPMC9320375 | biostudies-literature
Project description: Not available
| S-EPMC8557389 | biostudies-literature
Project description:This research note sheds light on the first three months of the COVID-19 outbreak in South Africa, where the virus has spread faster than anywhere else in the region. At the same time, South Africa has been recognized globally for its swift and efficient early response. We consider the impact of this response on different segments of the population, looking at changes in mobility by province to highlight variation in the willingness and ability of different subsets of the population to comply with lockdown orders. Using anonymized mobile phone data, we show that South Africans in all provinces reduced their mobility substantially in response to the government's lockdown orders. Statistical regression analysis shows that such mobility reductions are significantly and negatively associated with COVID-19 growth rates two weeks later. These findings add an important perspective to the emerging literature on the efficacy of shelter-in-place orders, which to date is dominated by studies of the United States. We show that people were particularly willing and able to act in the provinces hit hardest by the pandemic in its initial stages. At the same time, compliance with lockdown orders presented a greater challenge among rural populations and others with more precarious livelihoods. By reflecting on South Africa's inequality profile and results of a recent survey, we demonstrate how the country's response may deepen preexisting divides. This cautionary tale is relevant beyond South Africa, as much of the continent - and the world - grapples with similar tradeoffs. Along with measures to contain the spread of disease, governments and other development focused organizations should seriously consider how to offset the costs faced by already marginalized populations.
| S-EPMC7455114 | biostudies-literature
Project description:Following the highly restrictive measures adopted by many countries for combating the current pandemic, the number of individuals infected by SARS-CoV-2 and the associated number of deaths steadily decreased. This fact, together with the impossibility of maintaining the lockdown indefinitely, raises the crucial question of whether it is possible to design an exit strategy based on quantitative analysis. Guided by rigorous mathematical results, we show that this is indeed possible: we present a robust numerical algorithm which can compute the cumulative number of deaths that will occur as a result of increasing the number of contacts by a given multiple, using as input only the most reliable of all data available during the lockdown, namely the cumulative number of deaths.
| S-EPMC7444939 | biostudies-literature
Project description:This study quantifies the economic effect of a possible lockdown of Tokyo to prevent the spread of COVID-19. The negative effect of such a lockdown may propagate to other regions through supply chains because of supply and demand shortages. Applying an agent-based model to the actual supply chains of nearly 1.6 million firms in Japan, we simulate what would happen to production activities outside Tokyo if production activities that are not essential to citizens' survival in Tokyo were shut down for a certain period. We find that if Tokyo were locked down for a month, the indirect effect on other regions would be twice as large as the direct effect on Tokyo, leading to a total production loss of 27 trillion yen in Japan or 5.2% of the country's annual GDP. Although the production that would be shut down in Tokyo accounts for 21% of the total production in Japan, the lockdown would result in an 86% reduction of the daily production in Japan after one month.
| S-EPMC7491714 | biostudies-literature